# Artificial Intelligence (AI) Artificial Intelligence (AI) is the field of computer science focused on creating systems that can perform tasks requiring human-like intelligence—learning, reasoning, problem-solving, perception, and language understanding. The field was formally founded at the 1956 Dartmouth Conference, organized by [[John McCarthy]], [[Marvin Minsky]], [[Allen Newell]], and [[Herbert Simon]]. McCarthy coined the term "artificial intelligence" for this workshop. AI has evolved through multiple paradigms: symbolic AI (1950s-1980s) focused on logic and rules, connectionism and neural networks (1980s-2010s) on brain-inspired learning, and modern deep learning (2012-present) achieving breakthroughs in vision, language, and game-playing. The field intersects with [[Cognitive Psychology]], neuroscience, linguistics, and philosophy, raising profound questions about the nature of intelligence, consciousness, and the future of humanity. ## AI Timeline | Era | Period | Key Developments | |-----|--------|------------------| | **Foundations** | 1950s | Turing Test, Logic Theorist, Dartmouth Conference | | **Early AI** | 1960s | ELIZA, expert systems begin | | **First Winter** | 1970s | Funding cuts, scaled-back expectations | | **Expert Systems** | 1980s | Rule-based systems, commercial AI | | **Second Winter** | Late 1980s | Expert system limitations exposed | | **Machine Learning** | 1990s-2000s | Statistical approaches, SVMs, data-driven AI | | **Deep Learning** | 2012+ | ImageNet, AlphaGo, GPT, transformers | | **Foundation Models** | 2020s | Large language models, generative AI | ## Major Subfields | Subfield | Description | |----------|-------------| | **Machine Learning** | Systems that learn from data | | **Deep Learning** | Neural networks with many layers | | **Natural Language Processing** | Understanding and generating language | | **Computer Vision** | Interpreting visual information | | **Robotics** | Physical agents in the real world | | **Expert Systems** | Rule-based decision systems | | **Planning & Reasoning** | Goal-directed behavior | | **Speech Recognition** | Converting audio to text | ## Foundational Concepts - **[[Turing Test]]** (1950): Can a machine exhibit intelligent behavior indistinguishable from a human? - **Physical Symbol System Hypothesis**: Intelligence arises from symbol manipulation ([[Allen Newell]], [[Herbert Simon]]) - **Connectionism**: Intelligence emerges from networks of simple units - **Embodied AI**: Intelligence requires physical interaction with environment ## Types of AI | Type | Description | Examples | |------|-------------|----------| | **Narrow AI (ANI)** | Specialized for specific tasks | Chess engines, image classifiers | | **General AI (AGI)** | Human-level intelligence across domains | Hypothetical | | **Superintelligence (ASI)** | Exceeds human intelligence | Hypothetical | ## Key Figures | Person | Contribution | |--------|--------------| | [[Alan Turing]] | Turing Test, foundations of computation | | [[John McCarthy]] | Coined "AI", Lisp, time-sharing | | [[Marvin Minsky]] | Frames, Society of Mind | | [[Allen Newell]] | Logic Theorist, GPS, Soar | | [[Herbert Simon]] | Bounded rationality, GPS | | [[Geoffrey Hinton]] | Backpropagation, deep learning | | [[Yann LeCun]] | Convolutional neural networks | | [[Yoshua Bengio]] | Deep learning, attention mechanisms | ## Modern Breakthroughs - **2012**: AlexNet wins ImageNet, deep learning takes off - **2016**: AlphaGo defeats world Go champion - **2017**: Transformer architecture introduced - **2020**: GPT-3 shows emergent capabilities - **2022**: ChatGPT brings AI to mainstream - **2023-24**: Multimodal models, agents, reasoning ## References - https://en.wikipedia.org/wiki/Artificial_intelligence - https://en.wikipedia.org/wiki/History_of_artificial_intelligence - https://www.britannica.com/technology/artificial-intelligence ## Related - [[Allen Newell]] - [[Herbert Simon]] - [[Cognitive Psychology]] - [[Geoffrey Hinton]] - [[Turing Test]] - [[Alan Turing]] - [[Neural Networks (NNs)]] - [[Natural Language Processing (NLP)]] - [[Machine Learning (ML)]] - [[Deep Learning]]